Staggered Difference-in-Differences with Nonlinear Outcomes R package NonlinearDiD version 0.1.0 Implements difference-in-differences estimators for staggered treatment adoption with binary, count, and other nonlinear outcomes. Extends Callaway and Sant'Anna (2021) <doi:10.1016/j.jeconom.2020.12.001> to handle the fundamental identification challenges that arise with nonlinear outcome models (logit, probit, Poisson) in heterogeneous treatment timing designs. Provides group-time average treatment effects on the treated (ATT), aggregation schemes, and pre-treatment parallel trends tests appropriate for nonlinear settings. Methods include doubly-robust semiparametric estimators, nonparametric bounds, and an odds-ratio DiD approach for binary outcomes. Methods extend Callaway and Sant'Anna (2021) <doi:10.1016/j.jeconom.2020.12.001>, Roth and Sant'Anna (2023) <doi:10.3982/ECTA19255>, and Wooldridge (2023) <doi:10.1093/ectj/utad016>. Software Depends: R (>= 4.0.0) Imports: stats, utils, MASS, sandwich, lmtest, ggplot2, Rcpp (>= 1.0.0) LinkingTo: Rcpp Suggests: did, dplyr, knitr, rmarkdown, testthat (>= 3.0.0), covr Subir Hait <haitsubi@msu.edu> Comprehensive R Archive Network (CRAN) Subir Hait [aut, cre] (ORCID: <https://orcid.org/0009-0004-9871-9677>) MIT + file LICENSE (https://CRAN.R-project.org/package=NonlinearDiD/LICENSE) 2026-05-05 application/tgz https://CRAN.R-project.org/package=NonlinearDiD doi:10.32614/CRAN.package.NonlinearDiD